Import RD signal from bam/sam/cram file, calculate histograms, import SNPs form VCF file and calculate BAF histograms with specified bin size. Bin size should be larger then 5kbp to have enough SNPs per bin. We use 100kbp in this example:
> cnvpytor -root sample.pytor -rd sample.bam
> cnvpytor -root sample.pytor -his 100000
> cnvpytor -root sample.pytor -snp sample.vcf.gz
> cnvpytor -root sample.pytor -mask_snps
> cnvpytor -root sample.pytor -baf 100000
Run joint caller:
> cnvpytor -root sample.pytor -call combined 100000 > calls.tsv
Output format is illustrated here:
Full description of columns you can find in Geting started.
Enter interactive mode with one or multiple samples
> cnvpytor -root sample.pytor -view 100000
cnvpytor> set callers combined_mosaic # set caller to be used for ploting/exporting
cnvpytor> set Q0_range -1 0.5 # filter calls with more than half not uniqly maped reads
cnvpytor> set p_range 0 0.0001 # filter non-confident calls
cnvpytor> set size_range 500000 inf # filter calls smaller than 500kbp
cnvpytor> set dG_range 100000 inf # filter calls close to gaps in reference genome (<100kbp)
cnvpytor> print calls # printing calls on screen
...
...
cnvpytor> set print_filename calls.xlsx # Output filename (tsv, vcf or xlsx)
cnvpytor> print calls # Generate Excel output
cnvpytor> quit
File calls.xlsx contains list of filtered calls.
Enter interactive mode with one or multiple samples
> cnvpytor -root sample.pytor -view 100000
cnvpytor> set callers combined_mosaic # set caller to be used for ploting/exporting
cnvpytor> set Q0_range -1 0.5 # filter calls with more than half not uniqly maped reads
cnvpytor> set p_range 0 0.0001 # filter non-confident calls
cnvpytor> set size_range 500000 inf # filter calls smaller than 500kbp
cnvpytor> set dG_range 100000 inf # filter calls close to gaps in reference genome (<100kbp)
cnvpytor> set print_filename calls.vcf # Output filename
cnvpytor> set output_filename calls.png # Prefix for graphical output files
cnvpytor> set annotate # Turn on annotation (optional - takes a lot of time)
cnvpytor> set plot # Turn on ploting for each calls (optional - takes a lot of time)
cnvpytor> set panels rd likelihood # Set plotting panels
cnvpytor> print calls # Generate Excel output and png files with RD/likelihood plots
cnvpytor> quit
File calls.vcf contains filtered calls. Files calls.regions.0000.png, calls.regions.0001.png, contain RD/likelihood region plots for all calls.
Enter interactive mode with one or multiple samples:
> cnvpytor -root sample.pytor -view 100000
cnvpytor> set callers combined_mosaic # set joint caller
cnvpytor> set rd_range 0 4 # set rd range
cnvpytor> unset title # remove title (sample:region) from plot
cnvpytor> chr16:4m-10m # generate plot
This is an example of generated plot:
